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PDMS Unidirectional Antenna Array for Microwave Breast Screening

2022· article· en· W4308086691 on OpenAlexaff
Milad Mokhtari, Milica Popović

Bibliographic record

Venue2022 52nd European Microwave Conference (EuMC) · 2022
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsMcGill University
Fundersnot available
KeywordsAntenna (radio)Coplanar waveguideMicrowave imagingMicrowaveAntenna arrayAperture (computer memory)Breast tissueMaterials scienceComputer scienceElectronic engineeringOpticsAcousticsOptoelectronicsTelecommunicationsEngineeringPhysicsBreast cancerMedicine

Abstract

fetched live from OpenAlex

Microwave radar breast screening systems have been proposed as a safe, cost-efficient alternative to X-ray mammography. The hypothesis that underpins the operation of such systems relies on sensing the dielectric contrast between the malignant tumor and the healthy breast tissue. The vital element of the breast screening system is the sensing element, which transmits the microwave pulses into the breast tissue or collects the backscatter. In this paper, we propose an array of 16 coplanar waveguide (CPW) aperture-coupled patch antennas, aimed to operate in the 3–5 GHz range. The sensing element is designed to operate adjacent to the inhomogenous human breast tissue model. The planned fabrication of the antenna array on the flexible 5mm SYLGARD™ 184 silicone elastomer PDMS substrate will be followed with its integration with the transceiver circuitry. Simulations suggest that the near-field emissions from such antenna would effectively probe the lossy breast tissue, allowing for detection of the tumor via the back-scattered signals.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.202
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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Same venue2022 52nd European Microwave Conference (EuMC)Same topicWireless Body Area NetworksFrench-language works237,207